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Image Interpretation Using Bayesian Networks
January 1996 (vol. 18 no. 1)
pp. 74-77

Abstract—The problem of image interpretation is one of inference with the help of domain knowledge. In this correspondence, we formulate the problem as the maximum a posteriori (MAP) estimate of a properly defined probability distribution function. We show that a Bayesian network can be used to represent this p.d.f. as well as the domain knowledge needed for interpretation. The Bayesian network may be relaxed to obtain the set of optimum interpretations.

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Index Terms:
Artificial intelligence, Bayesian networks, expert systems, object recognition, image interpretation, decision making, inference systems, Markov random fields.
Citation:
V.p. Kumar, U.b. Desai, "Image Interpretation Using Bayesian Networks," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 18, no. 1, pp. 74-77, Jan. 1996, doi:10.1109/34.476423
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